A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria

Abstract The determination of the chronic toxicity is time-consumed and costly, so it’s of great interest to predict the chronic toxicity based on acute data. Current methods include the acute to chronic ratios (ACRs) and the QSTR models, both of which have some usage limitations. In this paper, the...

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Autores principales:	Dali Wang, Yue Gu, Min Zheng, Wei Zhang, Zhifen Lin, Ying Liu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8030a9497df64298ac68d94569644fd1
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spelling	oai:doaj.org-article:8030a9497df64298ac68d94569644fd12021-12-02T12:30:54ZA Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria10.1038/s41598-017-06384-92045-2322https://doaj.org/article/8030a9497df64298ac68d94569644fd12017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-06384-9https://doaj.org/toc/2045-2322Abstract The determination of the chronic toxicity is time-consumed and costly, so it’s of great interest to predict the chronic toxicity based on acute data. Current methods include the acute to chronic ratios (ACRs) and the QSTR models, both of which have some usage limitations. In this paper, the acute and chronic mixture toxicity of three types of antibiotics, namely sulfonamides, sulfonamide potentiators and tetracyclines, were determined by a bioluminescence inhibition test. A novel QSTR model was developed for predicting the chronic mixture toxicity using the acute data and docking-based descriptors. This model revealed a complex relationship between the acute and chronic toxicity, i.e. a linear correlation between the acute and chronic lg(−lgEC50)s, rather than the simple EC50s or −lgEC50s. In particular, the interaction energies (Ebind) of the chemicals with luciferase and LitR in the bacterial quorum sensing systems were introduced to represent their acute and chronic actions, respectively, regardless of their defined toxic mechanisms. Therefore, the present QSTR model can apply to the chemicals with distinct toxic mechanisms, as well as those with undefined mechanism. This study provides a novel idea for the acute to chronic toxicity extrapolation, which may benefit the environmental risk assessment on the pollutants.Dali WangYue GuMin ZhengWei ZhangZhifen LinYing LiuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Dali Wang Yue Gu Min Zheng Wei Zhang Zhifen Lin Ying Liu A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria
description	Abstract The determination of the chronic toxicity is time-consumed and costly, so it’s of great interest to predict the chronic toxicity based on acute data. Current methods include the acute to chronic ratios (ACRs) and the QSTR models, both of which have some usage limitations. In this paper, the acute and chronic mixture toxicity of three types of antibiotics, namely sulfonamides, sulfonamide potentiators and tetracyclines, were determined by a bioluminescence inhibition test. A novel QSTR model was developed for predicting the chronic mixture toxicity using the acute data and docking-based descriptors. This model revealed a complex relationship between the acute and chronic toxicity, i.e. a linear correlation between the acute and chronic lg(−lgEC50)s, rather than the simple EC50s or −lgEC50s. In particular, the interaction energies (Ebind) of the chemicals with luciferase and LitR in the bacterial quorum sensing systems were introduced to represent their acute and chronic actions, respectively, regardless of their defined toxic mechanisms. Therefore, the present QSTR model can apply to the chemicals with distinct toxic mechanisms, as well as those with undefined mechanism. This study provides a novel idea for the acute to chronic toxicity extrapolation, which may benefit the environmental risk assessment on the pollutants.
format	article
author	Dali Wang Yue Gu Min Zheng Wei Zhang Zhifen Lin Ying Liu
author_facet	Dali Wang Yue Gu Min Zheng Wei Zhang Zhifen Lin Ying Liu
author_sort	Dali Wang
title	A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria
title_short	A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria
title_full	A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria
title_fullStr	A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria
title_full_unstemmed	A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria
title_sort	mechanism-based qstr model for acute to chronic toxicity extrapolation: a case study of antibiotics on luminous bacteria
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/8030a9497df64298ac68d94569644fd1
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A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria

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